| 柴油机故障信号的形态学多尺度分形分析 |
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| 引用本文： | 史润泽.柴油机故障信号的形态学多尺度分形分析[J].兵工自动化,2019,38(9). |
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| 作者姓名： | 史润泽 |
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| 作者单位： | 中国人民解放军32382 部队，武汉 430311 |
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| 基金项目： | 国家自然科学基金(50705097)；河北省自然科学基金(E2007001048) |
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| 摘 要： | 为解决传统单一分形维数在表征信号时的缺陷，提出一种基于形态学计算的多尺度分形维数估计方法。
对柴油机正常、失火和气门间隙过大故障信号进行分析，并与单一分形维数方法进行对比。结果表明：基于形态学
计算的多尺度分形维数能准确地对柴油机不同状态下的信号进行分类，计算简单快速，具有很好的故障诊断效果。
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| 关 键 词： | 数学形态学 多尺度分形维数 柴油机 故障诊断 特征提取 |
| 收稿时间： | 2019/4/18 0:00:00 |
| 修稿时间： | 2019/5/23 0:00:00 |
Morphology Multi-scale Fractal Dimension Analysis on
Diesel Engine Fault Signal |
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| Abstract: | In order to solve the defect of traditional single fractal dimension in signal representation, a multi-scale
fractal dimension estimation method based on morphological calculation was proposed. The normal, misfire, and excessive
valve clearance fault signals of diesel engine were analyzed and compared with a single fractal dimension method. The
results show that the multi-scale fractal dimension based on morphological calculation can accurately classify the signals of
diesel engine in different states, and the calculation is simple and fast, which has good fault diagnosis effect. |
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| Keywords: | mathematical morphology multi-scale fractal dimension diesel engine fault diagnosis feature extraction |
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